Hepatitis b & c virus
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA556982 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The present study is aimed at profiling the miRNA expression pattern in oral squamous cell carcinoma (OSCC) and adjacent oral mucosa to develop a new miRNA signature for oral cancer. Agilent Human miRNA Microarray v2.0 (G4470B, Agilent Technologies) was used to identify miRNAs differentially expressed in OSCC. MicroRNA processing was carried out according to the manufacturer’s instructions. Hybridized microarrays were scanned with a DNA microarray scanner (Agilent G2565BA) and features were extracted using the Agilent Feature Extraction (AFE) image analysis tool (version A.9.5.3) with default protocols and settings. Data pre-processing and differential expression analysis were done in R Studio using the Bioconductor AgiMicroRna package.12 The Total Gene Signal provided by the AFE image analysis software was used for data analysis. Data were normalized between arrays using the quantile method. Microarray profiling identified a set of 105 miRNAs to be differentially expressed in OSCC, out of which a subset of 19 most dysregulated miRNAs were considered to formulate the miRNA signature for oral cancer.
2021-03-05 | GSE168227 | GEO
Project description:A global survey of alternative splicing of HBV transcriptome using Long-read sequencing
| PRJNA742195 | ENA
Project description:Analysis of Ultra-deep Pyrosequencing and Cloning Based Sequencing of the Basic Core Promoter/Precore/Core Region of Hepatitis B Virus Using Newly Developed Bioinformatics Tools
| PRJNA239442 | ENA
Project description:The ability to predict transcription factors based on sequence information in regulatory elements is a key step in systems-level investigation of transcriptional regulation. Here, we have developed a novel tool, IMAGE, for precise prediction of transcription factors based on transcriptome profiling and genome-wide maps of enhancer activity. High precision is obtained by combining a near-complete database of position weight matrices (PWMs), generated by compiling public databases and systematic prediction of PWMs for uncharacterized transcription factors, with a state-of-the-art method for PWM scoring and a novel machine learning strategy, based on both enhancers and promoters, to predict the contribution of motifs to transcriptional activity. We applied IMAGE to published data obtained during 3T3-L1 adipocyte differentiation and showed that IMAGE predicts causal transcriptional regulators of this process with higher confidence than other methods. Furthermore, we generated genome-wide maps of enhancer activity and transcripts during human mesenchymal stem cell commitment and adipocyte differentiation and used IMAGE to identify positive and negative transcriptional regulators of this process. Collectively, our results demonstrate that IMAGE is a powerful and precise method for prediction of regulators of gene expression.
2017-12-04 | GSE104537 | GEO
Project description:Purpose: To create a radiogenomic map linking computed tomographic (CT) image features and gene expression profiles generated by RNA sequencing for patients with non-small cell lung cancer (NSCLC). Methods: A cohort of 113 patients with NSCLC diagnosed between April 2008 and September 2014 who had preoperative CT data and tumor tissue available was studied. For each tumor, a thoracic radiologist recorded 87 semantic image features, selected to reflect radiologic characteristics of nodule shape, margin, texture, tumor environment, and overall lung characteristics. Next, total RNA was extracted from the tissue and analyzed with RNA sequencing technology. Ten highly coexpressed gene clusters, termed metagenes, were identified, validated in publicly available gene-expression cohorts, and correlated with prognosis. Next, a radiogenomics map was built that linked semantic image features to metagenes by using the t statistic and the Spearman correlation metric with multiple testing correction. Results: RNA sequencing analysis resulted in 10 metagenes that capture a variety of molecular pathways, including the epidermal growth factor (EGF) pathway. A radiogenomic map was created with 32 statistically significant correlations between semantic image features and metagenes. Conclusions: Radiogenomic analysis of NSCLC showed multiple associations between semantic image features and metagenes that represented canonical molecular pathways
2018-08-03 | GSE103584 | GEO
Project description:To compare 2 different image creation/processing techniques during a standard CT scan in order to "see" problems in the liver and learn which method provides better image quality. The techniques use new artificial intelligence software to decrease image noise, which helps the radiologist to evaluate.
| 2244256 | ecrin-mdr-crc
Project description:The lung is a branched tubular network with two distinct compartments — the proximal conducting airways and the peripheral gas exchange region — separated by a discrete boundary termed the bronchoalveolar duct junction (BADJ). Here we image the developing mouse lung in three-dimensions and show that two nested developmental waves demarcate the BADJ under the control of a global hormonal signal. A first wave of branching morphogenesis progresses throughout embryonic development, generating branches for both compartments. A second wave of conducting airway differentiation follows the first wave but terminates earlier, specifying the proximal compartment and setting the BADJ. The second wave is terminated by a glucocorticoid signaling: premature activation or loss of glucocorticoid signaling causes a proximal or distal shift, respectively, in BADJ location. The results demonstrate a novel mechanism of boundary formation in complex, three-dimensional organs and provide new insights into glucocorticoid therapies for lung defects in premature birth. RNAs were extracted from E14 lungs cultured in control and dexamethasone media for 24 hours using Trizol reagents and Qiagen RNeasy Micro kit. Two control and two treated samples were analyzed.
2014-05-22 | E-GEOD-56831 | biostudies-arrayexpress
Project description:Chronic liver disease and cancer are global health challenges. The role of the circadian clock (CC) as a regulator of physiology and disease is well established in animal models. However, in human liver the identity of circadian genes and their epigenetic regulation is unknown. Here, we unraveled the circadian transcriptome and epigenome of human hepatocytes using a human liver chimeric mouse model. We identified genes coding for transcription factors, chromatin modifiers, and critical enzymes which are expressed rhythmically in human hepatocytes, and which differ from the mouse liver circadian transcriptome. Moreover, we show that hepatitis C virus (HCV) infection, a major cause of liver disease and cancer world-wide, perturbs the human hepatocellular clock leading to an activation of pathways mediating steatosis, fibrosis and cancer. The HCV-disrupted rhythmic hepatic pathways remained deregulated in patients cured of HCV suggesting a major role in liver cancer development, and in the identification of therapeutic targets.
2024-08-02 | GSE200810 | GEO
Project description:MicroRNAs (miRNAs), including host miRNAs and viral miRNAs, play vital roles in regulating host-virus interactions. DNA viruses encode miRNAs that regulate the viral life cycle. However, it is generally believed that cytoplasmic RNA viruses do not encode miRNAs, owing to inaccessible cellular miRNA processing machinery. Here, we provide a comprehensive genome-wide analysis and identification of miRNAs that were derived from hepatitis A virus (HAV; Hu/China/H2/1982), which is a typical cytoplasmic RNA virus. Using deep-sequencing and in silico approaches, we identified 2 novel virally encoded miRNAs, named hav-miR-1-5p and hav-miR-2-5p. Both of the novel virally encoded miRNAs were clearly detected in infected cells. Analysis of Dicer enzyme silencing demonstrated that HAV-derived miRNA biogenesis is Dicer dependent. Furthermore, we confirmed that HAV mature miRNAs were generated from viral miRNA precursors (pre-miRNAs) in host cells. Notably, naturally derived HAV miRNAs were biologically and functionally active and induced post-transcriptional gene silencing (PTGS). Genomic location analysis revealed novel miRNAs located in the coding region of the viral genome. Overall, our results show that HAV naturally generates functional miRNA-like small regulatory RNAs during infection. This is the first report of miRNAs derived from the coding region of genomic RNA of a cytoplasmic RNA virus. These observations demonstrate that a cytoplasmic RNA virus can naturally generate functional miRNAs, as DNA viruses do. These findings also contribute to improved understanding of host-RNA virus interactions mediated by RNA virus-derived miRNAs.
2014-01-24 | GSE54368 | GEO